Brain Inspired

BI 215 Xiao-Jing Wang: Theoretical Neuroscience Comes of Age


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Xiao-Jing Wang is a Distinguished Global Professor of Neuroscience at NYU

Xiao-Jing was born and grew up in China, spent 8 years in Belgium studying theoretical physics like nonlinear dynamical systems and deterministic chaos. And as he says it, he arrived from Brussels to California as a postdoc, and in one day switched from French to English, from European to American culture, and physics to neuroscience. I know Xiao-Jing as a legend in non-human primate neurophysiology and modeling, paving the way for the rest of us to study brain activity related cognitive functions like working memory and decision-making.

He has just released his new textbook, Theoretical Neuroscience: Understanding Cognition, which covers the history and current research on modeling cognitive functions from the very simple to the very cognitive. The book is also somewhat philosophical, arguing that we need to update our approach to explaining how brains function, to go beyond Marr's levels and enter a cross-level mechanistic explanatory pursuit, which we discuss. I just learned he even cites my own PhD research, studying metacognition in nonhuman primates - so you know it's a great book. Learn more about Xiao-Jing and the book in the show notes. It was fun having one of my heroes on the podcast, and I hope you enjoy our discussion.

  • Computational Laboratory of Cortical Dynamics
  • Book: Theoretical Neuroscience: Understanding Cognition.
  • Related papers
    • Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory.
    • Macroscopic gradients of synaptic excitation and inhibition across the neocortex.
    • Theory of the multiregional neocortex: large-scale neural dynamics and distributed cognition.
    • 0:00 - Intro

      3:08 - Why the book now?
      11:00 - Modularity in neuro vs AI
      14:01 - Working memory and modularity
      22:37 - Canonical cortical microcircuits
      25:53 - Gradient of inhibitory neurons
      27:47 - Comp neuro then and now
      45:35 - Cross-level mechanistic understanding
      1:13:38 - Bifurcation
      1:24:51 - Bifurcation and degeneracy
      1:34:02 - Control theory
      1:35:41 - Psychiatric disorders
      1:39:14 - Beyond dynamical systems
      1:43:447 - Mouse as a model
      1:48:11 - AI needs a PFC

      ...more
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      Brain InspiredBy Paul Middlebrooks

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